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Customer value management (CVM) outlines the value journey that customers take and creates the best management approaches to every aspect of the journey. CVM creates best practices for handling every step from initial contact with prospects, whether through targeted marketing campaigns, the active sales cycle, or ongoing customer relationship management (CRM) after implementing solutions. 

The three stages of customer value management - value discovery, delivery, and realization - are clear collaborative stages that successfully measure customer value and the value of conversations, with conversational AI technology used to make these measurements. Value discovery focuses on the directional aspect of business value, with teams using efficient ways to gain unique insights into customer needs, framing conversations around potential outcomes, and quantifying value to encourage investment. Value delivery determines the solutions most beneficial to potential buyers and quantifies them based on customer input to create transparent use cases. Following successful implementation, value realization measures the actual value achieved compared to the baseline return on investment (ROI) model, providing business value that’s satisfactory to customers. 

Considering that most customers expect businesses to know their unique needs, customer value management helps teams quickly identify the value drivers that customers care about most and presents the how-to for teams to approach customers regarding a value conversation. Here are the dos and don’ts of customer value management you need to know. 

Do's - Ensuring CVM is More Value-Driven than Technology-Driven

While successful customer value management relies on technology to make it effective, relying excessively on the technology causes your team to lose focus on the goal: to provide highly-efficient solutions and use cases for customers.

Over time, customer value management became an increasingly integral solution-driven method for companies eager to provide value and benefits to customers in exchange for their loyalty. With problems becoming more complex and ways to map product capabilities, customer value management emerged as a more sophisticated way of leveraging value propositions relevant to customers and the organizations selling to them. 

While technology eases the challenges customers face, the focus should always be on selling value first, bringing organizations to quantify value for specific projects. Successfully analyzing and quantifying customer value depends on how well organizations frame their conversations to get the best insights and takeaways possible, making technology like conversational AI truly helpful. If conversations aren’t prioritizing value based on the right selling points, the technology can only help you so much. 

Dont’s - A Lack of Management Discipline 

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One of the most vital aspects of customer value management is having management discipline to properly execute it. With management discipline, businesses create customer-centric business models that prioritize value, making it a key aspect of internal processes. In conjunction with management discipline, businesses also must have strong programs to successfully cultivate customer value management as a skill. 

Without a constant emphasis on positioning value high within the customer journey or throughout every aspect of the sales cycle, customer value management loses its capabilities, causing businesses to lose track and diminish the quality of their customer conversations. 

Additionally, leaders must shift away from apportioning blame if things go wrong, preaching accountability across the board so that value-based models are created with the right approaches in mind, and teams can be more creative. 

Dos - Having Strong Data At Your Disposal 

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Customer value management takes the use of customer value as a strategic asset to higher levels, making it more attractive to teams. CVM applications are increasingly acting as repositories for all value data collected, easily and quickly generating case studies and value statements. 

For any customer value management approach to generate high success levels, having strong data touchpoints to go off from is a good start. The data can come from effectively measuring value attributed to existing numbers, using actual cost savings or performance to attach definitive figures. When new products or services are developed, the data could be based on customer expectations, then refined when the product/service reaches the marketplace. 

When prospect data is added to build a value proposition with the right targeting and delivery approaches, you garner reliably key performance indicators (KPIs) to help you best identify customer value. 

Don’ts - Failing to Satisfy Stakeholder Expectations 

If the customer value management approach you have doesn’t satisfy your stakeholder network, it immediately loses its viability. 

When measuring the success of CVM projects, sales teams must adopt and use CVM models as expected to boost close rates and achieve the ROI that was originally projected during the business case. When quantifying such success, stakeholders judge if the CVM approach reduced sales cycle time and exertion, improved closed rate percentages, and boosted conversion rates while also improving sales prices. 

Also, from a customer viewpoint, if the CVM strategy doesn’t garner improved cross-selling or upselling opportunities, or reduce churn, then stakeholders will likely be having a tense conversation with you about whether your strategy makes sense. 

Artificial intelligence provides the sort of conversational and business value that allows businesses to facilitate better teamwork while easing the tensions and uncertainties surrounding remote work. Versational provides a conversational assistant solution to ensure team leaders connect with their teams in the most effective ways possible and give employees the praise they deserve. Try our product for free today. 

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